Triple
T4642497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marigold |
E101685
|
entity |
| Predicate | hasTypicalUsageFrequency |
P28499
|
FINISHED |
| Object | rare |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: rare | Statement: [Marigold, hasTypicalUsageFrequency, rare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalUsageFrequency Context triple: [Marigold, hasTypicalUsageFrequency, rare]
-
A.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
B.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
-
C.
hasDailyUse
Indicates that something is used or occurs on a daily, regular basis.
-
D.
hasTypicalUseContext
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
-
E.
hasFrequencyCategory
chosen
Indicates that something is associated with a particular classification of how often it occurs or is used.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a93047c8190990c94fd5a57c867 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:14 p.m.